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        <h4 id="guide"><a href="#guide" class="headerlink" title="guide"></a>guide</h4><h4 id="语言进阶"><a href="#语言进阶" class="headerlink" title="语言进阶"></a>语言进阶</h4><h5 id="数据结构和算法"><a href="#数据结构和算法" class="headerlink" title="数据结构和算法"></a>数据结构和算法</h5><ul>
<li>算法：解决问题的方法和步骤</li>
<li>评价算法的好坏：渐进时间复杂度和渐进空间复杂度</li>
<li>排序算法（冒泡、选择和归并(分治法)）和查找算法（顺序和折半）</li>
</ul>
<p><strong>lambda函数</strong></p>
<p>匿名函数lambda：是指一类无需定义标识符（函数名）的函数或子程序。所谓匿名函数，通俗的说就是没有名字的函数，lambda函数没有名字，是一种 <strong>简单、在同一行中定义函数的</strong> 方式。</p>
<p>lambda函数可以接收任意多个参数（包括可选参数）并且返回单个表达式的值。</p>
<p><strong>lambda函数只允许包含一个表达式，不能包含复杂语句，该表示式的运算结果就是函数的返回结果。</strong></p>
<p>lambda函数基本的基本语法：<strong>lambda args1, args2, args3,…..: &lt;表达式&gt;</strong></p>
<p>一个栗子：</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">lambda x, y: x + y</span><br><span class="line">lambda:None # 函数没有输入参数，输出为 None</span><br><span class="line">lambda *args: sum(args) # 输入任意多个参数，输出是它们的和</span><br><span class="line">lambda **kargs: 1 # 输入任意多个键值对参数，输出为 1</span><br></pre></td></tr></table></figure>
<span id="more"></span>
<p><strong>常用算法</strong></p>
<ul>
<li>穷举法 - 又称为暴力破解法，对所有的可能性进行验证，知道找出正确答案</li>
<li>贪婪法 - 在对问题求解时，总是做出在当前看来</li>
<li>最好的选择，不求最优解，快速找到满意解。</li>
<li>分治法 - 把一个复杂的问题分成两个或更多的相同或相似的问题，再把子问题分成更小的子问题，直到可以直接求解的程度，最后将子问题的解进行合并得到原问题的解。</li>
<li>回溯法 - 回溯法又称为试探法，按优先条件向前搜索，当搜索到某一步发现原先选择并不优或者达不到目标时，就退回一步重新选择。</li>
<li>动态规划 - 基本思想也是将待求解问题分解成若干个子问题，先求解并保存这些子问题的解，避免产生大量的重复运算。</li>
</ul>
<p><strong>self 关键字的用法</strong></p>
<p>与普通的函数不同，在类中定义的函数，<strong>第一参数永远是类的本身实例变量<code>self</code></strong>,并且调用时，不用传递该参数。除此以外，类的方法（函数）和普通函数没有什么区别，你既可以用默认参数，也可以用可变参数与关键字参数（<strong>可变参数接收的是一个元组tuple，关键字接收的是一个字典。</strong>）</p>
<p>注意点：</p>
<ul>
<li><code>self</code> 代表类的实例，而非类。</li>
<li><code>self</code> 在定义时不可以省略。</li>
<li>在继承时，传入的是哪个实例，就是那个传入的实例，而不是指定义了 <code>self</code> 的类的实例。</li>
<li>在描述符类中，<code>self</code> 指的是描述符类的实例。</li>
</ul>
<p><strong>推导式 生成式</strong></p>
<ol>
<li><p>三元表达式</p>
 <figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">name=&#x27;abc&#x27;</span><br><span class="line">res=&#x27;SB&#x27; if name==&#x27;abc&#x27; else &#x27;NB&#x27;</span><br><span class="line">print(res)#SB</span><br></pre></td></tr></table></figure>
</li>
<li><p>列表推导式</p>
<p> 公式：[变量（加工后的变量）for 变量i in 可迭代的数据类型]</p>
 <figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># 求10以内所有的整数（不包括0）</span></span><br><span class="line">list1=[i <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">1</span>,<span class="number">11</span>)]</span><br><span class="line"><span class="built_in">print</span>(list1)<span class="comment">#[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]</span></span><br></pre></td></tr></table></figure>
</li>
<li><p>字典推导式</p>
 <figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">#将一个字典的key和value对调</span></span><br><span class="line">dict1=&#123;<span class="string">&#x27;a&#x27;</span>:<span class="number">10</span>,<span class="string">&#x27;b&#x27;</span>:<span class="number">20</span>,<span class="string">&#x27;c&#x27;</span>:<span class="number">30</span>,<span class="string">&#x27;d&#x27;</span>:<span class="number">40</span>&#125;</span><br><span class="line">swapDict=&#123;dict1[k]: k <span class="keyword">for</span> k <span class="keyword">in</span> dict1&#125;</span><br><span class="line"><span class="built_in">print</span>(swapDict)<span class="comment">#&#123;10: &#x27;a&#x27;, 20: &#x27;b&#x27;, 30: &#x27;c&#x27;, 40: &#x27;d&#x27;&#125;</span></span><br></pre></td></tr></table></figure>
</li>
<li><p>集合推导式</p>
 <figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">#将列表中的每个元素平方并去重</span></span><br><span class="line">squared=&#123;x**<span class="number">2</span> <span class="keyword">for</span> x <span class="keyword">in</span> [<span class="number">1</span>,-<span class="number">1</span>,<span class="number">2</span>]&#125;</span><br><span class="line"><span class="built_in">print</span>(squared)<span class="comment">#&#123;1,4&#125;</span></span><br></pre></td></tr></table></figure>
</li>
<li><p>生成器表达式</p>
<p> 把列表解析的[]换成（）得到的就是生成器表达式</p>
<p> 列表解析与生成器表达式都是一种便利的编程方式，只不过生成器表达式更节省内存</p>
 <figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">result=[i <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">1</span>,<span class="number">6</span>)]</span><br><span class="line">obj=(i <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">1</span>,<span class="number">6</span>))</span><br><span class="line"><span class="built_in">print</span>(obj)<span class="comment">#&lt;generator object &lt;genexpr&gt; at 0x00000000021DF678&gt;</span></span><br><span class="line"><span class="built_in">print</span>(<span class="built_in">list</span>(obj))<span class="comment">#[1, 2, 3, 4, 5]</span></span><br></pre></td></tr></table></figure>
</li>
</ol>
<h5 id="函数的使用方式"><a href="#函数的使用方式" class="headerlink" title="函数的使用方式"></a>函数的使用方式</h5><p><img src="http://localhost:4000/2020/10/30/python/函数的使用方式.png" alt></p>
<ul>
<li>将函数视为 “一等公民”<ul>
<li>函数可以赋值给变量</li>
<li>函数可以作为函数的参数</li>
<li>函数可以作为函数的返回值</li>
</ul>
</li>
<li>高阶函数的用法（<code>filter</code>、<code>map</code>以及它们的替代品）</li>
<li>位置参数、可变参数、关键字参数、命名关键字参数</li>
<li>参数的元信息（代码可读性问题）</li>
<li>匿名函数和内联函数的用法（<code>lambda</code>函数）</li>
<li>闭包和作用域的问题</li>
<li>装饰器函数（使用装饰器和取消装饰器）</li>
</ul>
<h6 id="with-关键字的使用"><a href="#with-关键字的使用" class="headerlink" title="with 关键字的使用"></a>with 关键字的使用</h6><p>with表达式其实就是<code>try-finally</code>的简写形式，但又不是完全相同。</p>
<p>格式</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line"><span class="string">&quot;&quot;&quot;</span></span><br><span class="line"><span class="string">格式</span></span><br><span class="line"><span class="string">with context [as var]:</span></span><br><span class="line"><span class="string">    pass</span></span><br><span class="line"><span class="string">&quot;&quot;&quot;</span></span><br></pre></td></tr></table></figure>
<blockquote>
<p>其中的context是一个表达式，返回的是一个对象，var用来保存context表达式返回的对象，可以有单个或者多个返回值。</p>
</blockquote>
<h5 id="面向对象相关知识"><a href="#面向对象相关知识" class="headerlink" title="面向对象相关知识"></a>面向对象相关知识</h5><p><img src="http://localhost:4000/2020/10/30/python/面向对象相关知识.png" alt></p>
<h5 id="迭代器和生成器"><a href="#迭代器和生成器" class="headerlink" title="迭代器和生成器"></a>迭代器和生成器</h5><h5 id="并发编程"><a href="#并发编程" class="headerlink" title="并发编程"></a>并发编程</h5><h4 id="Web前端概述"><a href="#Web前端概述" class="headerlink" title="Web前端概述"></a>Web前端概述</h4>
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